Tag: England

I just heard a talk by social network creator extraordinaire Clio Andris about redefining regional boundaries in the UK based on telecommunications data. Her group took data from 12 billion telephone calls made over the space of a month and created a social network based on this (Ratti et al. , 2010). This network was then used to calculate how closely connected two neighbouring locations were. By optimising the spectral modularity, the best-fitting boundaries could be defined.

One of the first things that struck me was the similarity with a map of regional accents (apologies for the quality of the accent map – I couldn’t find the one I was looking for). Apparently, people are talking to people that sound like them. Or, people who talk to each other sound like each other. This isn’t covered in the paper, but seems like an important issue.

Secondly, the rail links also seem to form the ‘backbones’ of the communications regions. This is also mentioned in the paper. However, these two features are linked.

Coming from Wales, the important fit here is the three-way split in Wales. South Wales feels like a different country to North Wales – culturally and linguistically. However, both are linked by having large amounts of natural resources: Coal in South Wales and slate in North Wales. This lead to massive migration into cities in the north and south, and rail links were set up to extract these resources to London or the nearest ports: Cardiff in the south and Liverpool in the north. Thus, it’s still a real pain to get from North Wales to South Wales. The picture is somewhat true of the east and west sides of the north of England.

So, the natural resources concentrated people and transport links. However, it also concentrated political views. The large migrant community in Wales, working for little pay in large mine institutions, became unionised. Socialism emerged, promoting political movements that lead to the minimum wage.

The point being, natural resources, transport links and politics are connected with some being historically dependent on each other. This is, perhaps, precisely why splitting the nation by who speaks to who is a good measure of political regions. It would be fascinating to see how linguistic divisions interact with these variables.

In mylast postI outlined a number of experimental studies using the Zebra Finch that have highlighted an additional dimension to the FoxP2 gene – not only is it upregulated in the avian brain throughout song development, but it is also downregulated in important song nuclei of adult birds in singing contexts that seem to involve ‘listening to one’s own song’ and subsequent error correction. Given that the pattern of expression of this gene is very similar in the developing brain of both humans and birds, one conclusion that has been drawn from this research is that FOXP2 downregulation may equivocally serve to facilitate online language processing function in the adult human brain.

General background on an intriguing new celebrity

Naturally, the next step has been to try and identify the downstream genes regulated by FOXP2 in order to build up a more detailed picture of how interactions between complex genetic networks influence key language-related disorders in humans. It is as a result of such efforts that another gene, although discovered almost a decade ago, has found its way into the spotlight: CNTNAP2.

In the developing human brain, CNTNAP2 is enriched in functionally specialised regions such as the frontal cortex, the stratium, and the dorsal thalamus (circuits within these regions are referred to as cortico-striato-thalmic circuits) central to executive function, planning and executing complex sequential movements, and thus potentially, language. This presents a striking contrast to the more uniform expression of Cntnap2 observed in the developing rodent brain where there is no evidence for enrichment in specific regions, suggesting a functional difference in the human version that could be related to vocal learning and modification.

Shared or collective intentionality is the ability and motivation to engage with others in collaborative, co-operative activities with joint goals and intentions. (Tomasello et al. 2005). The term also implies that the collaborators’ psychological processes are jointly directed at something and take place within a joint attentional frame (Hurford 2007: 320, Tomasello et al. 2005).

What makes humans unique? This never-ending debate has sparked a long list of proposals and counter-arguments and, to quote from a recent article on this topic,

“a similar fate most likely awaits some of the claims presented here. However such demarcations simply have to be drawn once and again. They focus our attention, make us wonder, and direct and stimulate research, exactly because they provoke and challenge other researchers to take up the glove and prove us wrong.” (Høgh-Olesen 2010: 60)

In this post, I’ll focus on six candidates that might play a part in constituting what makes human cognition unique, though there are countless others (see, for example, here).

One of the key candidates for what makes human cognition unique is of course language and symbolicthought. We are “the articulate mammal” (Aitchison 1998) and an “animal symbolicum” (Cassirer 2006: 31). And if one defining feature truly fits our nature, it is that we are the “symbolic species” (Deacon 1998). But as evolutionary anthropologists Michael Tomasello and his colleagues argue,

“saying that only humans have language is like saying that only humans build skyscrapers, when the fact is that only humans (among primates) build freestanding shelters at all” (Tomasello et al. 2005: 690).

Language and Social Cognition

According to Tomasello and many other researchers, language and symbolic behaviour, although they certainly are crucial features of human cognition, are derived from human beings’ unique capacities in the social domain. As Willard van Orman Quine pointed out, language is essential a “social art” (Quine 1960: ix). Specifically, it builds on the foundations of infants’ capacities for joint attention, intention-reading, and cultural learning (Tomasello 2003: 58). Linguistic communication, on this view, is essentially a form of joint action rooted in common ground between speaker and hearer (Clark 1996: 3 & 12), in which they make “mutually manifest” relevant changes in their cognitive environment (Sperber & Wilson 1995). This is the precondition for the establishment and (co-)construction of symbolic spaces of meaning and shared perspectives (Graumann 2002, Verhagen 2007: 53f.). These abilities, then, had to evolve prior to language, however great language’s effect on cognition may be in general (Carruthers 2002), and if we look for the origins and defining features of human uniqueness we should probably look in the social domain first.

Corroborating evidence for this view comes from comparisons of brain size among primates. Firstly, there are significant positive correlations between group size and primate neocortex size (Dunbar & Shultz 2007). Secondly, there is also a positive correlation between technological innovation and tool use – which are both facilitated by social learning – on the one hand and brain size on the other (Reader and Laland 2002). Our brain, it seems, is essential a “social brain” that evolved to cope with the affordances of a primate social world that frequently got more complex (Dunbar & Shultz 2007, Lewin 2005: 220f.).

Thus, “although innovation, tool use, and technological invention may have played a crucial role in the evolution of ape and human brains, these skills were probably built upon mental computations that had their origins and foundations in social interactions” (Cheney & Seyfarth 2007: 283).

I came across this rather amusing model for predicting football results using mostly economic data (click on image for full screen):

Now, we all know Brazil aren’t going to win the world cup, but most of us would’ve predicted they’d fare quite well, and possibly win it (my own failed prediction was with Argentina). What’s dubious about the algorithm their using is it predicted Serbia to be finalists! How the hell did they arrive at that conclusion? Well, to give you an indication they do discuss some of the factors included in the model. I’ll definitely be coming back to this when I’ve got a spare moment… They did, however, predict Germany would face, and subsequently knock out, England in the last 16.

If the Bank of England cuts interest rates on Thursday could the interest paid on our savings fall below zero?

Negative interest rates, where the bank charges us to look after our savings, have been seen before.

In the 1970s Swiss banks charged foreign customers rather than paying them interest to hold their money.

I don’t think we’ll see negative interest rates in the UK, although it is technically possible, and has happened before. To use the hypothetical example offered by the BBC: if you place £10,000 in the bank, and the negative interest rate is at -1%, then at the end of the year you’d get a return of just £9,900 — essentially a £100 charge for the pleasure of banking. Great.